PIETERJORIS.IO
Technology is best when it brings people together. Technology should serve people, not the other way around.
20 years in technology and business has shown me that the balance is often skewed. Today I see it turned into a weapon: on real battlefields, and in the quieter battle for our attention and our divisions.Twenty years in presales and business development across BeNeLux gave me a front-row seat to that shift. Now I'm taking the time to build again to figure out how I can contribute to technology that actually brings people and organizations together.
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Based in Brussels, at the heart of Europe. That front-row seat ran through Fujitsu-Siemens Computers, then Fujitsu Technology Solutions, and closed at Fsas Technologies in May 2026. Same employer on paper, though ownership, portfolio, and the way of working shifted more than once underneath it
That work put me close to the gap between what technology promises and what it delivers for the people meant to benefit from it. I still believe in what it can do. I've also seen, up close, how often it doesn't.
I'm a father to twin daughters, five years old. It's why I think in decades, not quarters, and why I'd rather build something they can trust than something that's fast.
Right now, I'm not in a hurry for the next role. I'm using this space deliberately to think and build. On my own terms.
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A few things I'm building and thinking through right now. Some concrete, some still taking shape.
Most of this runs on, or started in, my own homelab: Proxmox for hosting, layered backup through Proxmox Backup Server and NAS-based targets, local LLM inference via Ollama and Open WebUI, n8n for automation.
They're where a lot of my current thinking gets tested in practice.
I keep coming back to one question in particular: who actually controls the data and the models an organization depends on, and what happens when they don't. It's not a fixed direction, and not a service I'm offering yet. One of several paths I'm still weighing, next to BD/GTM leadership, advisory work, teaching. No rush to commit.
AI models & systems that don't just respond but act, chaining decisions and tool use with less human oversight at each step. The sovereignty questions get sharper here: who sets an agent's boundaries, what happens when it fails quietly, how much autonomy an organization can responsibly hand over. Still exploring rather than building a practice around it, but it's increasingly the lens through which I look at the evolution of AI applications in organizations.
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I write, occasionally, about the same tension that runs through the rest of this: technology, its promise, and its limits.
Longer-form pieces live on Substack — the first one is up, more will follow. Shorter, more frequent thoughts go out on LinkedIn.
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If something here resonates, or you just want to compare notes, I'd like to hear from you.